The accuracy of wind speed forecasting is related to the wind power scheduling. When large-scale wind power connected grid, it also affects the stability of the grid. This paper applies time series model and Back Propagation (BP) neural network model to predict wind speed. Finally, a combination model of time series and BP neural network is proposed. In the combination model, the inputs of BP neural network are made up of historical data and residual errors calculated by time series model. The model can be more accurately in the short-time wind speed forecasting. And then shows an actual example. Keywords-wind speed forecasting; time series model; BP neural network model; combination model Ⅰ. INTRODUCTION At present, the development of wind power industry is rapid in China. But wind energy is unstable. The large-scale wind power connected grid will bring problem about the stability of the grid. The electricity sector need to understand the coming hours output of wind power. Then can give the reasonable scheduling scheme. So there is need to study the prediction wind power. The first step is to forecast wind speed in the prediction. There are a lot of wind speed forecasting methods, such as time series [1,2,3,4,5], Kalman filter method[6], Weibull distribution method [7,8], neural network [9,10,11], etc. As the random distribution of wind speed, the mentioned forecasting methods have their own limitations. This paper proposes a combination model of time series and BP neural network. The inputs of BP neural network are made up of historical data and residual errors calculated by time series model. The model can be more accurately to predict the short-time wind speed. Ⅱ. WIND SPEED TIME SERIES MODEL Time series model used to forecast wind speed is relatively simple. Only need a single time series of wind speed. According to Box.Jenkins method, time series can be divided into: AR (auto regression), MA (moving average), and ARMA (auto regression moving average). Time series model used to forecast wind speed mainly includes modeling and smooth processing, model order determination and parameters estimation.
Objective: To explore the clinical effect of integrated traditional Chinese and Western medicine in the treatment of liver-stomach disharmony functional dyspepsia. Methods: Sixty patients with functional dyspepsia of liver-stomach disharmony type admitted to our hospital from January to August 2022 were selected as research subjects and randomly divided into two groups, a study group and a control group, with 30 cases in each group. The main observations were stomachache or pain over bilateral flanks, emotionally depressed, belching, fullness and discomfort over the abdomen and flanks, acid regurgitation, loss of appetite, frequent sighing, noisy epigastric, and the treatment effect. Results: According to the classification of symptom severity on the traditional Chinese medicine (TCM) symptom score table, statistics were made on the corresponding severity of the main symptoms and secondary symptoms of the two groups of patients, and the data of the two groups were compared by Wilcoxon test. The results showed that there was no significant difference in the distribution of TCM symptoms between the two groups; the study group’s total effective rate of pain relief (recovery + markedly effective + effective) was 96.67%, and Fisher’s ?2 test indicated a significant difference in the total effective rate of pain relief between the two groups (P = 0.027 < 0.05). Conclusion: The use of integrated traditional Chinese and western medicine is clearly better than the simple application of western medicine. It is safe and has no side effects. It can be used as a treatment for patients with functional dyspepsia.
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